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Optimal budget allocation for discrete-event simulation experiments

Author

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  • Chun-Hung Chen
  • Enver Yücesan
  • Liyi Dai
  • Hsiao-Chang Chen

Abstract

Simulation plays a vital role in analyzing discrete-event systems, particularly in comparing alternative system designs with a view to optimizing system performance. Using simulation to analyze complex systems, however, can be both prohibitively expensive and time-consuming. Effective algorithms to allocate intelligently a computing budget for discrete-event simulation experiments are presented in this paper. These algorithms dynamically determine the simulation lengths for all simulation experiments and thus significantly improve simulation efficiency under the constraint of a given computing budget. Numerical illustrations are provided and the algorithms are compared with traditional two-stage ranking-and-selection procedures through numerical experiments. Although the proposed approach is based on heuristics, the numerical results indicate that it is much more efficient than the compared procedures.

Suggested Citation

  • Chun-Hung Chen & Enver Yücesan & Liyi Dai & Hsiao-Chang Chen, 2010. "Optimal budget allocation for discrete-event simulation experiments," IISE Transactions, Taylor & Francis Journals, vol. 42(1), pages 60-70.
    • Handle: RePEc:taf:uiiexx:v:42:y:2010:i:1:p:60-70
    DOI: 10.1080/07408170903116360
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    Cited by:

    1. Shing Chih Tsai & Chen Hao Kuo, 2012. "Screening and selection procedures with control variates and correlation induction techniques," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(5), pages 340-361, August.
    2. Zhang, Rui & Chiang, Wen-Chyuan & Wu, Cheng, 2014. "Investigating the impact of operational variables on manufacturing cost by simulation optimization," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 634-646.
    3. Qiushi Chen & Lei Zhao & Jan C. Fransoo & Zhe Li, 2019. "Dual-mode inventory management under a chance credit constraint," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 147-178, March.

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